Deductive Module Extraction for Expressive Description Logics
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
Main track. Pages 1636-1643. https://doi.org/10.24963/ijcai.2020/227
In deductive module extraction, we determine a small subset of an ontology for a given vocabulary that preserves all logical entailments that can be expressed in that vocabulary. While in the literature stronger module notions have been discussed, we argue that for applications in ontology analysis and ontology reuse, deductive modules, which are decidable and potentially smaller, are often sufficient. We present methods based on uniform interpolation for extracting different variants of deductive modules, satisfying properties such as completeness, minimality and robustness under replacements, the latter being particularly relevant for ontology reuse. An evaluation of our implementation shows that the modules computed by our method are often significantly smaller than those computed by existing methods.
Knowledge Representation and Reasoning: Description Logics and Ontologies